Adaption of the OMOP CDM for Rare Diseases

Zoch, Michéle; Gierschner, Christian; Peng, Yuan; Gruhl, Mirko; Leutner, Liz A.; Sedlmayr, Martin; Bathelt, Franziska

doi:10.3233/shti210136

Cited by 6 publications

(10 citation statements)

References 13 publications

(14 reference statements)

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“…To improve disease diagnostic capabilities for the greatest number of people, larger and more diverse cohorts are needed ( Zoch et al, 2021 ). By facilitating international cooperation via secure data unification, federation can support more diverse population representation in genomic datasets ( Vesteghem et al, 2020 ; Asiimwe et al, 2021 ; Garden, 2021 ; Powell, 2021 ; Zoch et al, 2021 ; Lee et al, 2022 ).…”

Section: Overcoming Secure Data Sharing Via Federa...mentioning

confidence: 99%

Democratizing clinical-genomic data: How federated platforms can promote benefits sharing in genomics

Alvarellos¹,

Sheppard²,

Knarston³

et al. 2023

Front. Genet.

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Since the first sequencing of the human genome, associated sequencing costs have dramatically lowered, leading to an explosion of genomic data. This valuable data should in theory be of huge benefit to the global community, although unfortunately the benefits of these advances have not been widely distributed. Much of today’s clinical-genomic data is siloed and inaccessible in adherence with strict governance and privacy policies, with more than 97% of hospital data going unused, according to one reference. Despite these challenges, there are promising efforts to make clinical-genomic data accessible and useful without compromising security. Specifically, federated data platforms are emerging as key resources to facilitate secure data sharing without having to physically move the data from outside of its organizational or jurisdictional boundaries. In this perspective, we summarize the overarching progress in establishing federated data platforms, and highlight critical considerations on how they should be managed to ensure patient and public trust. These platforms are enabling global collaboration and improving representation of underrepresented groups, since sequencing efforts have not prioritized diverse population representation until recently. Federated data platforms, when combined with advances in no-code technology, can be accessible to the diverse end-users that make up the genomics workforce, and we discuss potential strategies to develop sustainable business models so that the platforms can continue to enable research long term. Although these platforms must be carefully managed to ensure appropriate and ethical use, they are democratizing access and insights to clinical-genomic data that will progress research and enable impactful therapeutic findings.

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Section: Overcoming Secure Data Sharing Via Federa...mentioning

confidence: 99%

Democratizing clinical-genomic data: How federated platforms can promote benefits sharing in genomics

Alvarellos¹,

Sheppard²,

Knarston³

et al. 2023

Front. Genet.

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“…This datamodel is essential in the context of rare diseases due to the current lack of catalogs with the needed terminologies. 11 All datapoints were transformed in Athena-ID's, complying with the OMOP CDM standards.…”

Section: Datamodel and Databasementioning

confidence: 99%

Validation of an Artificial Intelligence driven framework to automatically detect red flag symptoms in screening for rare diseases in electronic health records: hereditary transthyretin amyloidosis polyneuropathy as a key example

Hens¹,

Wyers²,

Claeys

2022

J Peripheral Nervous Sys

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Rare life-threatening conditions, such as multisystemic hereditary transthyretin amyloidosis (ATTRv) polyneuropathy, are often underdiagnosed or diagnosed late in the disease course, although early diagnosis is crucial for treatment success. Red flag symptoms have been identified, but manual screening of multidisciplinary medical records on this set of symptoms is time-consuming. This study aimed to

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“…The ETL stage deals with the database conversion from the EHR to CDM. Research attempts have been made by mapping vocabularies with CDM components following an ETL framework [10], addressing issues during the conversion process [11], or evaluating the feasibility of implementation in various aspects (e.g., data quality) [12][13][14]. Among the few papers that discuss CDM application after ETL, Zhang et al [7] extract data from a Chinese hospital to examine treatment pathways of three chronic diseases.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the rare attempts to leverage CDM for process mining purposes, it will become more crucial to be able to adopt CDM as the transition of healthcare data sources continues [10][11][12][13]20]. Consequently, the need for a universal method for event log preparation and analysis in the midst of CDM's growing presence will increase as well.…”

Section: Introductionmentioning

confidence: 99%

Exploring the potential of OMOP common data model for process mining in healthcare

et al. 2023

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Background and objective Recently, Electronic Health Records (EHR) are increasingly being converted to Common Data Models (CDMs), a database schema designed to provide standardized vocabularies to facilitate collaborative observational research. To date, however, rare attempts exist to leverage CDM data for healthcare process mining, a technique to derive process-related knowledge (e.g., process model) from event logs. This paper presents a method to extract, construct, and analyze event logs from the Observational Medical Outcomes Partnership (OMOP) CDM for process mining and demonstrates CDM-based healthcare process mining with several real-life study cases while answering frequently posed questions in process mining, in the CDM environment. Methods We propose a method to extract, construct, and analyze event logs from the OMOP CDM for process types including inpatient, outpatient, emergency room processes, and patient journey. Using the proposed method, we extract the retrospective data of several surgical procedure cases (i.e., Total Laparoscopic Hysterectomy (TLH), Total Hip Replacement (THR), Coronary Bypass (CB), Transcatheter Aortic Valve Implantation (TAVI), Pancreaticoduodenectomy (PD)) from the CDM of a Korean tertiary hospital. Patient data are extracted for each of the operations and analyzed using several process mining techniques. Results Using process mining, the clinical pathways, outpatient process models, emergency room process models, and patient journeys are demonstrated using the extracted logs. The result shows CDM’s usability as a novel and valuable data source for healthcare process analysis, yet with a few considerations. We found that CDM should be complemented by different internal and external data sources to address the administrative and operational aspects of healthcare processes, particularly for outpatient and ER process analyses. Conclusion To the best of our knowledge, we are the first to exploit CDM for healthcare process mining. Specifically, we provide a step-by-step guidance by demonstrating process analysis from locating relevant CDM tables to visualizing results using process mining tools. The proposed method can be widely applicable across different institutions. This work can contribute to bringing a process mining perspective to the existing CDM users in the changing Hospital Information Systems (HIS) environment and also to facilitating CDM-based studies in the process mining research community.

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Adaption of the OMOP CDM for Rare Diseases

Cited by 6 publications

References 13 publications

Democratizing clinical-genomic data: How federated platforms can promote benefits sharing in genomics

Democratizing clinical-genomic data: How federated platforms can promote benefits sharing in genomics

Validation of an Artificial Intelligence driven framework to automatically detect red flag symptoms in screening for rare diseases in electronic health records: hereditary transthyretin amyloidosis polyneuropathy as a key example

Exploring the potential of OMOP common data model for process mining in healthcare

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